We have proposed RIAV-MVS, a novel learning-based MVS method. Our approach exploits a convolutional GRU to iteratively optimize the index fields of the cost volume for depth regression. The cost volume construction is further improved via the incorporation of a transformer block to the reference image and a residual pose network to correct the relative poses. The extensive experiments on ScanNet [1]}, 7-Scenes [2]} and RGB-D Scenes V2 [3]} have demonstrated the superior accuracy and cross-dataset generalization capability of our method.
